{"id":"W2080147937","doi":"10.1080/00036840701522861","title":"Determinants of housing price volatility in Canada: a dynamic analysis","year":2008,"lang":"en","type":"article","venue":"Applied Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Economics; Volatility (finance); Econometrics; Variance decomposition of forecast errors; Autoregressive conditional heteroskedasticity; Heteroscedasticity; Skewness; Volatility swap; Volatility smile; Granger causality; Autoregressive model; Price level; Financial economics; Macroeconomics; Implied volatility","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000451825,0.0002119447,0.001023962,0.0004498734,0.00008376523,0.00001665673,0.0003029776,0.000106416,0.0001550375],"category_scores_gemma":[0.00002638058,0.0003012806,0.0001496322,0.0004653794,0.00007685678,0.0001551361,0.00008697737,0.0001467836,0.00003676276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001353016,"about_ca_system_score_gemma":0.0004199342,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4498452,"about_ca_topic_score_gemma":0.8951121,"domain_scores_codex":[0.9976897,0.000008021866,0.001318868,0.0005322444,0.00001910221,0.0004321059],"domain_scores_gemma":[0.9985824,0.00008600226,0.0006956264,0.0005246894,0.0000130798,0.00009823213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003383732,0.00004388456,0.9894808,0.00002067118,0.00009536155,0.000003272702,0.0002311922,0.007100454,0.000003565392,0.001576771,0.00001361034,0.001396574],"study_design_scores_gemma":[0.0005539546,0.000009445725,0.831571,0.000003666389,0.0000249903,0.000003101497,0.0001091743,0.1634418,0.00009865817,0.003253727,0.0005339349,0.0003965603],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9736553,0.00007923578,0.0004417843,0.00002085946,0.0001663473,0.0001734362,0.0001002142,0.00001443687,0.02534842],"genre_scores_gemma":[0.9984974,0.0004613385,0.0008377167,0.00008621111,0.00001878552,0.0000144048,0.00001737788,0.00003123613,0.00003556318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4452669,"threshold_uncertainty_score":0.9999439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01749324096203411,"score_gpt":0.1870477783954011,"score_spread":0.169554537433367,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}